Document similarity measures are very important in the field of information retrieval and search engines. They are measures that tell us how similar to documents are in terms of their word content. They can be used to find similar documents or to find how close a document is to a query on a search engine. There are many of such measures.

• This class contains the following:

  • A constructor that takes a file name and loads the words in it (ignoring punctuation and turning text to lower case).
  • A constructor that takes a string and loads it
  • Functions to add a string to the set, remove a string from the set, clear the entire set, return the number of strings in the set, and output all strings in the set.
  • The + operator overloaded to return the union of two StringSet objects.
  • The '*' operator overloaded to return the intersection of two StringSet objects.
  • A function to compute the similarity between the current StringSet and an input parameter of type StringSet.

• Similarity is measured by binary cosine coefficient. The coefficient is a value between 0 and 1, where 1 indicates that the query (or document) is very similar to the document and 0 indicates that the query has no keywords in common with the document.

• Once we have a query Q represented as a set of words and a document D represented as a set of words (each word counts once even if repeated in document multiple times), the similarity between Q and D is computed by:

  • Sim = |Q ∩ D| The size of set of common words / (sqrt size of D * sqrt size of Q)